Internal combustion engines combust a fuel and air mixture within cylinders driving pistons to produce drive torque. The engine drives a transmission through a coupling device. In the case of an automatic transmission, the coupling device includes a torque converter. The transmission transfers the drive torque to a driveline through one of a plurality of gear ratios. The transmission shifts between gear ratios based on a shift schedule and vehicle operating conditions.
The transmission typically includes a plurality of clutches that are selectively engaged to establish a desired gear ratio. When shifting between gear ratios, clutch-to-clutch shifts may occur. More specifically, at least one clutch is disengaged (i.e., off-going clutch) while another clutch is concurrently engaged (i.e., on-coming clutch). Control of the clutch-to-clutch shift is based on many shift parameters including, but not limited to, estimated engine torque, a clutch fill time, a clutch pressure offset and a clutch full feed fill threshold pressure.
Electronically controlled transmissions may have self-learning algorithms that are designed to optimize the quality of gear shift events by altering a controlled parameter such as commanded pressure to one or more of the clutches. The self-learning algorithms can broadly be divided into categories including shift quality error detection, selection of parameters to adjust and magnitude of adjustment. It may be beneficial to provide an improved method of error detection.